老年队列哮喘急性发作患者的共病模式及其预后影响
2025/06/16
摘要
背景：哮喘经常与导致哮喘控制不佳和生活质量低下的疾病共存。哮喘急性加重指的是疾病严重恶化的发作期。目前，很少有研究专注于确定哮喘的多病共存模式并评估它们对哮喘恶化的影响。
目的：识别老年队列中与哮喘发作相关的不同多病共存模式，并评估它们对预后的影响。
方法：本研究是一项回顾性队列研究，对纳入的849例哮喘患者的合并症进行了Mini Batch K-Means聚类分析，并进行Logistic回归分析以量化已确定的表型与结果之间的独立关联。
结果：本研究在哮喘患者中识别出四种共病模式。聚类1（N=232，27.33%）、2（N=122，14.37%）、3（N=149，17.55%）和4（N=346，40.75%）的特征分别是以过敏为主、呼吸系统为主、心脏代谢为主和合并症较少。第2组重症监护病房收治风险（比值比[OR]，2.30）、无创通气（OR，2.68）、机械通气（OR，1.93）和1年内因哮喘急诊再就诊率（OR，3.10）的风险显著增加。第3组患者1年内因合并症再入院风险（OR，2.53）及因共病再就诊于急诊的风险（OR，1.84）最高。
结论：本研究识别出4种与老年哮喘急性发作患者的临床特征和不良结局相关的多病共存模式。合并症可以被认为是可治疗特质，有助于最大限度地降低未来恶化的风险和哮喘的不良影响。
关键词：哮喘;聚类分析;加重;影响;多病共存模式
文献来源：（Ge Y, Zuo R, Xi H, et al. Multimorbidity Patterns of Asthma Exacerbation in an Older Cohort: Prognostic Implications. J Allergy Clin Immunol Pract. Published online April 8, 2025. doi:10.1016/j.jaip.2025.03.047）
Abstract
Background:Asthma frequently coexists with other diseases associated with poor asthma control and low quality of life. Asthma exacerbation refers to severe episodes of disease worsening. Few studies have focused on identifying multimorbidity patterns in asthma and assessing their effects on asthma exacerbations.
Objective:To identify distinct multimorbidity patterns associated with asthma exacerbation in an older cohort and evaluate their impact on prognosis.
Methods:We performed a Mini Batch K-Means clustering analysis of the comorbidities of 849 patients with asthma in this retrospective cohort study. Logistic regression analysis was performed to quantify independent associations between the identified phenotypes and outcomes.
Results:We identified four multimorbidity patterns in patients with asthma. Clusters 1 (N=232, 27.33%), 2 (N=122, 14.37%), 3 (N=149, 17.55%), and 4 (N=346, 40.75%) were characterized by predominantly allergic, predominantly respiratory, predominantly cardiometabolic, and fewer comorbidities, respectively. Clusters 2 was at a significantly increased risk of intensive care unit admission (odds ratio [OR], 2.30), noninvasive ventilation (OR, 2.68), mechanical ventilation (OR, 1.93) and 1-year ED revisits for asthma (OR, 3.10). Cluster 3 had the highest risk of 1-year readmission for comorbidities (OR, 2.53) and one-year ED revisit for comorbidities (OR, 1.84).
Conclusion:We identified four multimorbidity patterns associated with clinical characteristics and adverse outcomes in patients at risk for asthma exacerbations. Comorbidities can be recognized as treatable traits that can minimize the risk of future exacerbations and the adverse effects of asthma.
Keywords:Asthma; clustering analysis; exacerbation; impacts; multimorbidity patterns.
背景：哮喘经常与导致哮喘控制不佳和生活质量低下的疾病共存。哮喘急性加重指的是疾病严重恶化的发作期。目前，很少有研究专注于确定哮喘的多病共存模式并评估它们对哮喘恶化的影响。
目的：识别老年队列中与哮喘发作相关的不同多病共存模式，并评估它们对预后的影响。
方法：本研究是一项回顾性队列研究，对纳入的849例哮喘患者的合并症进行了Mini Batch K-Means聚类分析，并进行Logistic回归分析以量化已确定的表型与结果之间的独立关联。
结果：本研究在哮喘患者中识别出四种共病模式。聚类1（N=232，27.33%）、2（N=122，14.37%）、3（N=149，17.55%）和4（N=346，40.75%）的特征分别是以过敏为主、呼吸系统为主、心脏代谢为主和合并症较少。第2组重症监护病房收治风险（比值比[OR]，2.30）、无创通气（OR，2.68）、机械通气（OR，1.93）和1年内因哮喘急诊再就诊率（OR，3.10）的风险显著增加。第3组患者1年内因合并症再入院风险（OR，2.53）及因共病再就诊于急诊的风险（OR，1.84）最高。
结论：本研究识别出4种与老年哮喘急性发作患者的临床特征和不良结局相关的多病共存模式。合并症可以被认为是可治疗特质，有助于最大限度地降低未来恶化的风险和哮喘的不良影响。
关键词：哮喘;聚类分析;加重;影响;多病共存模式
文献来源：（Ge Y, Zuo R, Xi H, et al. Multimorbidity Patterns of Asthma Exacerbation in an Older Cohort: Prognostic Implications. J Allergy Clin Immunol Pract. Published online April 8, 2025. doi:10.1016/j.jaip.2025.03.047）
（南方医科大学南方医院 胡玉玲 龚钊乾 赵文驱）
Abstract
Background:Asthma frequently coexists with other diseases associated with poor asthma control and low quality of life. Asthma exacerbation refers to severe episodes of disease worsening. Few studies have focused on identifying multimorbidity patterns in asthma and assessing their effects on asthma exacerbations.
Objective:To identify distinct multimorbidity patterns associated with asthma exacerbation in an older cohort and evaluate their impact on prognosis.
Methods:We performed a Mini Batch K-Means clustering analysis of the comorbidities of 849 patients with asthma in this retrospective cohort study. Logistic regression analysis was performed to quantify independent associations between the identified phenotypes and outcomes.
Results:We identified four multimorbidity patterns in patients with asthma. Clusters 1 (N=232, 27.33%), 2 (N=122, 14.37%), 3 (N=149, 17.55%), and 4 (N=346, 40.75%) were characterized by predominantly allergic, predominantly respiratory, predominantly cardiometabolic, and fewer comorbidities, respectively. Clusters 2 was at a significantly increased risk of intensive care unit admission (odds ratio [OR], 2.30), noninvasive ventilation (OR, 2.68), mechanical ventilation (OR, 1.93) and 1-year ED revisits for asthma (OR, 3.10). Cluster 3 had the highest risk of 1-year readmission for comorbidities (OR, 2.53) and one-year ED revisit for comorbidities (OR, 1.84).
Conclusion:We identified four multimorbidity patterns associated with clinical characteristics and adverse outcomes in patients at risk for asthma exacerbations. Comorbidities can be recognized as treatable traits that can minimize the risk of future exacerbations and the adverse effects of asthma.
Keywords:Asthma; clustering analysis; exacerbation; impacts; multimorbidity patterns.
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识别与哮喘2型嗜酸性炎症相关的支气管上皮基因
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早期临床缓解与延缓肺功能下降和降低哮喘急性加重风险相关
